Checkpoint blockade and microsatellite instability

ABSTRACT

Blockade of immune checkpoints such as cytotoxic T-lymphocyte antigen-4 (CTLA-4) and programmed death-1 (PD-1) shows promise in patients with cancer. Inhibitory antibodies directed at these receptors have been shown to break immune tolerance and promote anti-tumor immunity. These agents work particularly well in patients with a certain category of tumor. Such tumors may be particularly susceptible to treatment because of the multitude of neoantigens which they produce.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/131,339, filed Dec. 22, 2020, which is a continuation of U.S.application Ser. No. 16/144,549, filed Sep. 27, 2018, now U.S. Pat. No.10,934,356, issued Mar. 2, 2021, which is a continuation of U.S.application Ser. No. 15/523,451, filed May 1, 2017, which is a NationalStage application under 35 U.S.C. § 371 of International Application No.PCT/US2015/060331, having an International Filing Date of Nov. 12, 2015,which claims the benefit of priority of U.S. Provisional Application No.62/190,977, filed Jul. 10, 2015 and U.S. Provisional Application No.62/079,357, filed Nov. 13, 2014, each of which are incorporated hereinby reference in their entirety.

This invention was made with government support under grants CA043460and CA062924 awarded by the National Institutes of Health. Thegovernment has certain rights in the invention.

TECHNICAL FIELD OF THE INVENTION

This invention is related to the area of cancer. In particular, itrelates to cancer therapy.

BACKGROUND OF THE INVENTION

Microsatellite instability (MSI) is the accumulation of sequencingerrors in microsatellites. This occurs in tumors with deficiency in DNAmismatch repair. MSI is present in Lynch Syndrome which is an inheritedcancer syndrome that predisposes patients to colon, endometrial, gastriccancer, ovarian, small intestine, liver, hepatobiliary, upper urinarytract, brain, and prostate cancer. MSI is also present in 10-20% ofsporadic colorectal, gastric, prostate, lung, ampullary, and endometrialcancers. Between 0.3% and 13% of pancreatic cancers are reported to beMSI as well.

The importance of intact immune surveillance in controlling outgrowth ofneoplastic transformation has been known for decades. Accumulatingevidence shows a correlation between tumor-infiltrating lymphocytes(TILs) in cancer tissue and favorable prognosis in various malignancies.In particular, the presence of CD8+ T-cells and the ratio of CD8+effector T-cells/FoxP3+ regulatory T-cells seems to correlate withimproved prognosis and long-term survival in solid malignancies such asovarian, colorectal and pancreatic cancer, hepatocellular carcinoma,malignant MEL and RCC. TILs can be expanded ex vivo and re-infused,inducing durable objective tumor responses in cancers such as melanoma.

The PD-1 receptor-ligand interaction is a major pathway hijacked bytumors to suppress immune control. The normal function of PD-1,expressed on the cell surface of activated T-cells under healthyconditions, is to down-modulate unwanted or excessive immune responses,including autoimmune reactions. The ligands for PD-1 (PD-L1 and PD-L2)are constitutively expressed or can be induced in various tumors.Binding of either PD-1 ligand to PD-1 inhibits T-cell activationtriggered through the T-cell receptor. PD-L1 is expressed at low levelson various non-hematopoietic tissues, most notably on vascularendothelium, whereas PD-L2 protein is only detectably expressed onantigen-presenting cells found in lymphoid tissue or chronicinflammatory environments. PD-L2 is thought to control immune T-cellactivation in lymphoid organs, whereas PD-L1 serves to dampenunwarranted T-cell function in peripheral tissues. Although healthyorgans express little (if any) PD-L1, a variety of cancers weredemonstrated to express abundant levels of this T-cell inhibitor. Highexpression of PD-L1 on tumor cells (and to a lesser extent of PD-L2) hasbeen found to correlate with poor prognosis and survival in variouscancer types, including renal cell carcinoma (RCC), pancreaticcarcinoma, hepatocellular carcinoma, ovarian carcinoma and non-smallcell lung cancer (NSCLC). Furthermore, PD-1 has been suggested toregulate tumor-specific T cell expansion in patients with malignant MELThe observed correlation of clinical prognosis with PD-L1 expression inmultiple cancers suggests that the PD-1/PD-L1 pathway plays a criticalrole in tumor immune evasion and should be considered as an attractivetarget for therapeutic intervention.

Blockade of immune checkpoints such as cytotoxic T-lymphocyte antigen-4(CTLA-4) and programmed death-1 (PD-1) is showing promise in patientswith cancer. CTLA-4 and PD-1 are upregulated on activated T cells andprovide inhibitory signals to T cells undergoing activation. Inhibitoryantibodies directed at these receptors have been shown to break immunetolerance and promote anti-tumor immunity. MK-3475 is a humanizedmonoclonal IgG4 antibody against PD-1 and is showing activity inmultiple tumor types including melanoma and non-small cell lung cancer(NSCLC). Previously, activity of a different PD-1 blocking antibody,BMS-936558, a fully humanized monoclonal IgG4 antibody, also showedactivity in melanoma, NSCLC, and a complete response in a single patientwith colorectal cancer.

MK-3475 (previously known as SCH 900475) is a potent andhighly-selective humanized mAb of the IgG4/kappa isotype designed todirectly block the interaction between PD-1 and its ligands, PD-L1 andPD-L2. MK-3475 contains the S228P stabilizing mutation and has noantibody-dependent cell-mediated cytotoxicity (ADCC) orcomplement-dependent cytotoxicity (CDC) activity. MK-3475 stronglyenhances T lymphocyte immune responses in cultured blood cells fromhealthy human donors, cancer patients, and primates. In T-cellactivation assays using human donor blood cells, the EC50 was in therange of 0.1 to 0.3 nM. MK-3475 also modulates the level ofinterleukin-2 (IL-2), tumor necrosis factor alpha (TNFα), interferongamma (IFNγ), and other cytokines. The antibody potentiates existingimmune responses only in the presence of antigen and does notnonspecifically activate T-cells.

The programmed death 1 (PD-1) pathway is a negative feedback systemrepressing Th1 cytotoxic immune responses that, if unregulated, coulddamage the hose¹⁻³. It is upregulated in many tumors and theirsurrounding microenvironment. Blockade of this pathway with antibodiesto PD-1 or its ligands has led to remarkable clinical responses in somepatients with many different cancer types, including melanomas,non-small cell lung cancer, renal cell carcinoma, bladder cancer andHodgkin's lymphoma⁴⁻¹⁰. The expression of ligands to PD-1 (PD-L1 orPD-L2) on the surface of tumor cells or immune cells is important butnot a definitive predictive biomarker for response to PD-1blockade^(4,6-8,11).

We were intrigued that, in reports of the effects of PD-1 blockade inhuman tumors, only one of 33 colorectal cancer (CRC) patients respondedto this treatment, in contrast to substantial fractions of patients withmelanomas, renal cell cancers, and lung tumors.^(10,12). What wasdifferent about this single patient? We hypothesized that this patienthad MMR-deficiency, because MMR-deficiency occurs in a small fraction ofadvanced CRCs,^(13,14) somatic mutations found in tumors can berecognized by the patient's own immune system,¹⁵ and MMR-deficientcancers have 10- to 100-fold more somatic mutations than MMR-proficientCRC.¹⁶⁻¹⁸ Moreover, MMR-deficient cancers contain prominent lymphocyteinfiltrates, consistent with an immune response¹⁹⁻²². And two of thetumor types that were most responsive to PD-1 blockade in a study byTopalian et al.¹⁰ had high numbers of somatic mutations as a result ofexposure to cigarette smoke (lung cancers) or UV radiation(melanomas)^(23,24). Our hypothesis was correct: the tumor of the singleCRC patient who responded to PD-1 blockade was MMR-deficient²⁵. Wetherefore hypothesized that MMR-deficient tumors are more responsive toPD-1 blockade than are MMR-proficient tumors.

To test this hypothesis, we initiated a phase 2 clinical trial toevaluate immune checkpoint blockade in patients whose tumors had or didnot have MMR-deficiency. Since MMR deficiency in tumors arises throughtwo routes²⁶⁻²⁸, we recruited patients with Hereditary Non-PolyposisColorectal Cancer (HNPCC, also known as Lynch Syndrome), which resultsfrom an inherited germline defect in one of four MMR genes followed by asecond inactivating somatic change in the remaining wild-type allele. Wealso recruited patients with sporadic MMR-deficient tumors, where bothalleles of a MMR gene are inactivated by somatic mutations or byepigenetic silencing²⁹. In either case, the neoplasms that arise harborhundreds or thousands of mutations^(16,18).

There is a continuing need in the art to improve cancer treatments sothat the lives of patients are not curtailed and so that the quality oflife is not diminished.

SUMMARY OF THE INVENTION

According to one embodiment of the invention a method of treating acancer patient is provided. The cancer patient has a high mutationalburden, such as found in microsatellite instable cancer (MSI). An immunecheckpoint inhibitory antibody is administered to the cancer patient.

According to another embodiment of the invention a method of treating acancer patient is provided. A sample from a cancer patient is tested forone or more microsatellite markers selected from the group consisting ofBAT-25, BAT-26, MONO-27, NR-21, NR-24, Penta C, and Penta D, anddetermined to have microsatellite instability. The cancer is selectedfrom the group consisting of: colon, gastric, endometrial,cholangiocarcinoma, pancreatic, and prostate cancers. An anti-PD-1antibody is administered to the cancer patient.

According to another embodiment of the invention a method is providedfor categorizing a tumor of a human. A sample from the human is testedto evaluate stability of one or more microsatellite markers.Microsatellite instability is determined in the sample. The tumor isidentified as a good candidate for treatment with an immune checkpointinhibitory antibody.

According to yet another embodiment of the invention a method isprovided for categorizing a tumor of a human. A sample from the human istested to evaluate stability of one or more microsatellite markers.Microsatellite stability in the sample is determined. The tumor isidentified as a bad candidate for treatment with an immune checkpointinhibitory antibody.

These and other embodiments which will be apparent to those of skill inthe art upon reading the specification provide the art with methods fortreating microsatellite instable cancers.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1B. Clinical Responses to pembrolizumab. (FIG. 1A) BiochemicalResponses. Serum protein biomarker levels were measured with each cycleand the values represent percent change from baseline. Patients wereincluded if baseline tumor marker values were greater than the upperlimit of normal. CA-125 was used for a patient with endometrial cancer;CA19-9 was used for one cholangiocarcinoma and one ampullary cancer; andCEA was used for all other patients. Green, red, and black linesrepresent patients with MMR-deficient CRCs, MMR-proficient CRCs, andMMR-deficient non-CRC, respectively. (FIG. 1B) Radiographic responses.Tumor responses were measured at regular intervals and values show thebest fractional change of the sum of longest diameters (SLD) from thebaseline measurements of each measurable tumor.

FIGS. 2A-2D. Clinical benefit to pembrolizumab according to MMR status.Kaplan-Meier curves are shown for (FIG. 2A) progression-free survival inthe colorectal cancer cohorts, (FIG. 2B) overall survival in thecolorectal cancer cohorts, (FIG. 2C) progression-free survival ofpatients with MMR-deficient cancers other than colorectal (medianPFS=5.4 months; 95% CI, 3% to not estimable), and (FIG. 2D) overallsurvival of patients with MMR-deficient cancers other than colorectal.In both cohorts with MMR-deficient tumors (CRC and non-CRC), medianoverall survival was not reached. Patients in the cohort withMMR-proficient cancers had a median PFS of 2.2 months (95% CI 1.4 to2.8%) and a median OS of 5.0 months (95% CI 3.0 to not estimable).

FIG. 3 (Figure S2.) Spider plot of radiographic response. Tumorresponses were measured at regular intervals and values show percentchange of the sum of longest diameters (SLD) from the baselinemeasurements of each measurable tumor. Patients were only included ifbaseline and on study treatment scans were available. Green and redrepresent patients with MMR-deficient and proficient CRCs, respectively.Blue represents patients with MMR-deficient cancers other than CRC.

FIGS. 4A-4B (Figure S3). MMR-proficient and deficient CRCs havecomparable time on treatment and duration of metastatic disease prior tostudy enrollment. Kaplan-Meier estimates of (FIG. 4A) time on therapyimmediately prior to study enrollment (HR 0.81, 95% CI 0.38 to 1.752,p=0.60) and (FIG. 4B) duration of metastatic disease prior to enrollment(HR 1.13, 95% CI 0.49 to 2.62, p=0.78) on this pembrolizumab study werecomparable between the MMR-deficient and proficient CRC cohorts. Theshort duration on prior therapy is expected in a treatment refractoryCRC population.

FIG. 5 (Figure S4.) Waterfall plot of biochemical response. Serumprotein biomarker levels were measured with each cycle and the valuesrepresent best percent change from baseline. Patients were included ifbaseline tumor marker values were greater than the upper limit ofnormal. CA-125 was used for a patient with endometrial cancer; CA19-9was used for 1 cholangiocarcinoma and 1 ampullary cancer; and CEA wasused for all other patients. Green and red represent patients withMMR-deficient and proficient CRCs, respectively. Blue representspatients with MMR-deficient cancers other than CRC.

FIGS. 6A-6B (Figure S5.) Somatic mutations in MMR-deficient andproficient tumors. Total somatic mutations per tumor identified by exomesequencing of tumor and matched normal DNA (FIG. 6A) and correlationwith objective responses (FIG. 6B) (non-parametric Wilcoxon test,p=0.007 and Jonckheere-Terpstra test for trend, p=0.02).

FIG. 7 (Figure S6). Immunohistochemistry of CD8 and PD-L1 Expression.The invasive front (yellow dashed line) from a MMR-deficient CRC(subject #16, top) and MMR-proficient CRC (subject #3, bottom). Theyellow dashed line separates tumor (T) and normal (N) tissue. There ismarked expression of PD-L1 (blue arrows) and CD8 (brown dots) in theMMR-deficient tumor (top panels) patient while there is very littleexpression of either marker in the MMR-proficient tumor (bottom panels).Representative images of tumor infiltrating lymphocytes (TIL) in anotherMMR-deficient CRC (subject #19, top) and MMR-proficient CRC (subject #3,bottom) immunolabeled with an antibody to CD8 (brown dots). Note theinfiltration of CD8 cells in the MMR-deficient tumor. Invasive frontoriginal magnification 10× and TIL 20×.

FIG. 8 (Figure S7.) CD8 and PD-L1 Expression in the MMR-deficient andMMR-proficient tumor microenvironment. T cell density units arecells/mm2 of tumor. Invasive front refers to the immune cells (TILs andmacrophages) at the junction of the tumor and normal tissue. P-valuesobtained using an unpaired t-test.

FIG. 9 (Figure S8.) CD8 expression and clinical benefit topembrolizumab. Correlation between the intratumoral CD8⁺ T cell density(cells/mm2) and objective response (Jonckheere-Terpstra test for trend,p=0.02).

FIG. 10 (Table S1.) Comparison of immune-related and RECIST responsecriteria (adapted from Wolchok et al. Clin Can Res 2009; 15:7412-20.)

FIG. 11 (Table S2.) Immune-Related response to treatment

FIG. 12 (Table S4.) Correlation of total somatic mutations and mutationassociated neoantigens (MANA) with clinical outcomes

FIG. 13 (Table S5.) Correlation of immune markers with clinical outcome

DETAILED DESCRIPTION OF THE INVENTION

The inventors have found that immune checkpoint inhibitors work best intumors with high mutation burdens. Furthermore, tumors deficient inmismatch repair are particularly susceptible to a particular form ofimmunotherapy because this phenotype results in ongoing accumulation ofmutations at a high frequency. The inventors have developed a treatmentfor cancer patients that display the microsatellite instabilityphenotype or other high mutational burden. The treatment involves aninhibitory antibody for an immune checkpoint. Such checkpoints includePD-1, IDO, CTLA-4, PD-L1, and LAG-3. Other immune checkpoints can beused as well. Antibodies can be administered by any means that isconvenient, including but not limited to intravenous infusion, oraladministration, subcutaneous administration, sublingual administration,ocular administration, nasal administration, etc.

Microsatellite instability (MSI) tumors are deficient in DNA mismatchrepair which leads to a high rate of spontaneous mutations and thepotential for the expression of neo-antigens. Furthermore, similar tomelanoma, in MSI positive colon cancers, there is often prominentlymphocyte infiltration. Any tumors that are MSI or otherwise highmutational burden may be treated according to the invention. They may betested for the attribute of MSI according to any method known in theart, including but not limited that described in example 1 below. Any ofone or more MSI markers can be tested to determine an MSI phenotype.Samples may be tested for high mutational burden by identifying tumorswith at least 100, at least 200, at least 300, at least 400, at least500, at least 600, at least 700, at least 800, at least 900, at least1000, at least 1100, at least 1200, at least 1300, at least 1400, atleast 1500, or at least 1600 mutations per tumor genome. High mutationalburden means a large number of somatic mutations in the tumor relativeto normal tissues of the individual. An average number of somaticmutations in a non-MSI tumor is about 70 somatic mutations.

Any type of tumor that displays the MSI phenotype or a high mutationalburden may be tested and/or treated according to the invention. Theseinclude without limitation cancers of the colon, gastric, endometrial,cholangiocarcinoma, pancreatic, and prostate cancer. Tumors of theampulla, biliary, brain, including glioma, breast, lung, skin,esophagus, liver, kidney, ovaries, sarcoma, uterus, cervix, bladder,testes, oral cavity, tongue, and small and large bowel may also betested and/or treated.

Testing of MSI can be accomplished by any means known in the art. One ormore of the following markers may be tested: five nearly monomorphicmononucleotide repeat markers (BAT-25, BAT-26, MONO-27, NR-21 and NR-24)and two highly polymorphic pentanucleotide repeat markers (Penta C andPenta D). In one commercial system which can be used, fluorescentlylabeled primers (marker panel) are used for co-amplification of allseven of the above named markers. Fragments are detected afteramplification for assignment of genotype/phenotype.

Samples that can be tested for MSI include tumor tissue as well as bodyfluids that contain nucleic acids shed from tumors. Testing for tumorDNA in such tissues and body fluids is well known.

Types of antibodies which can be used include any that are developed forthe immune checkpoint inhibitors. These can be monoclonal or polyclonal.They may be single chain fragments or other fragments of fullantibodies, including those made by enzymatic cleavage or recombinantDNA techniques. They may be of any isotype, including but not limited toIgG, IgM, IgE. The antibodies may be of any species source, includinghuman, goat, rabbit, mouse, cow, chimpanzee. The antibodies may behumanized or chimeric. The antibodies may be conjugated or engineered tobe attached to another moiety, whether a therapeutic molecule or atracer molecule. The therapeutic molecule may be a toxin, for example.

The data from the small phase 2 trial of pembrolizumab to treat tumorswith and without deficiency of MMR supports the hypothesis thatMMR-deficient tumors are more responsive to PD-1 blockade than areMMR-proficient tumors. MMR-deficiency occurs in many cancers, includingthose of the colorectum, uterus, stomach, biliary tract, pancreas,ovary, prostate and small intestine^(18,34-42). Patients withMMR-deficient tumors of these types also benefit from anti-PD-1 therapy,as may patients whose tumors contain other DNA repair deficiencies, suchas those with mutations in POLD, POLE, or MYH.^(18,43,44)

The hypothesis that MMR-deficient tumors stimulate the immune system isnot a new idea⁴⁵, and has been supported by the dense immuneinfiltration and Th1-associated cytokine-rich environment observed inMMR-deficient tumors.^(19-22,46) A recent study refined these classicobservations by showing that the MMR-deficient tumor microenvironmentstrongly expressed several immune checkpoint ligands including PD-1,PD-L1, CTLA-4, LAG-3 and IDO, indicating that their active immunemicroenvironment is counterbalanced by immune inhibitory signals thatresists tumor elimination⁴⁷. That the immune infiltrate associated withMMR-deficient carcinomas was directed at neoantigens was the most likelyexplanation for both the old and new findings. The correlation of highermutational load and higher response rate to anti-CTLA-4 in melanoma⁴¹and anti-PD-1 in lung cancer⁴⁸ provide further support for the idea thatMANA recognition is an important component of the endogenous anti-tumorimmune response.

Based on the results of the current and previous studies, we suggestthat the greatly (>20-fold) increased number of mutation-associatedneoantigens resulting from MMR deficiency (FIG. 12 (Table S4); alsoavailable on line at New England Journal of Medicine; incorporated byreference herein) is the basis for the enhanced anti-PD-1 responsivenessof this genetically defined subset of cancers. Though our estimates forthe number of mutation-associated neoantigens in tumors is based only onin silico predictions of binding-affinity, this suggestion is consistentwith the observation that MMR-proficient tumors have far lessinfiltration of lymphocytes than MMR-deficient tumors (FIG. 7 (S6), FIG.8 (S7) and FIG. 13 (Table S5); available on line at New England Journalof Medicine; incorporated by reference herein). Recent studies^(49,50)show that only a tiny proportion of predicted neo-epitopes are actuallypresented on the cell surface with MEW and are targets of endogenous Tcell responses. It seems likely, though that the number of predictedmutation-associated neoantigens is proportionate to the number of actualmutation-associated neoantigens, and tumors with a high number of actualmutation-associated neoantigens are more likely to stimulate the immunesystem to react against the tumor. Alternative mechanisms underlying thedifference in anti-PD-1 responsiveness between MMR-deficient andMMR-proficient tumors should also be considered. For example, differentsignaling pathways activated in MMR-deficient and MMR-proficient tumorsmay result in differences in secretion of soluble factors that couldresult in differential activation of the PD-1 pathway within the tumormicroenvironment²⁶⁻²⁸. Genetic differences could effect epigeneticdifferences that alter the expression of tumor-associated self-antigensthat in turn could alter the antigenicity of the tumor. Experimentalanalyses of antigen-specific immune responses as well as changes inimmune microenvironments should help to define the relative contributionof these factors to the striking responsiveness of MMR-deficient tumorsto PD-1 antibodies.

Several notable observations were made during the course of this study.First, changes in serum protein biomarkers, like CEA, corresponded withclinical benefit after a single dose of therapy. Declines in CEA levelspreceded objective radiographic evidence by several months; perhapsother biomarkers such as circulating tumor DNA (ctDNA) may also bebeneficial as surrogate markers of early response.^(51,52) Second, ourresults suggest that the evaluation of tumor genomes can help guideimmunotherapy. They support the view that the number and type ofalterations may prove useful for judging the potential utility of immunecheckpoint inhibitors, even in MMR-proficient cancers^(41,48,53) Mostimportantly, our results demonstrate a new approach for the treatment ofa specific class of tumors based solely on genetic status: i.e., withoutregard to underlying tumor type.

The above disclosure generally describes the present invention. Allreferences disclosed herein are expressly incorporated by reference. Amore complete understanding can be obtained by reference to thefollowing specific examples which are provided herein for purposes ofillustration only, and are not intended to limit the scope of theinvention.

Example 1

MSI Testing

MSI testing is already standardized and performed in CLIA-certifiedlaboratories without need for assay development. Archived tumor samplesor newly obtained biopsies will be used for determining MSI. MSI statuswill be performed locally by CLIA certified immunohistochemistry (IHC)or PCR based tests for eligibility. Evaluable patients will be confirmedusing the MSI Analysis System from Promega at Johns Hopkins. This testwill determine MSI status through the insertion or deletion of repeatingunits in the five nearly monomorphic mononucleotide repeat markers(BAT-25, BAT-26, MONO-27, NR-21 and NR-24). At least 2 MSI loci arerequired to be evaluable in Cohorts A and C. Patients may be assigned toa new cohort and/or replaced based on the Promega test results.

Example 2

Methods

Patients

Treatment-refractory progressive metastatic cancer patients for thisphase 2 study were recruited from three participating centers (Table 1).Three cohorts were evaluated: Cohort A was composed of patients withMMR-deficient colorectal adenocarcinomas; Cohort B was composed ofpatients with MMR-proficient colorectal adenocarcinomas; and Cohort Cwas composed of patients with MMR-deficient cancers of types other thancolorectal.

Study Oversight

The protocol, which can be found at NEJM.org, was approved by eachsite's institutional review boards, and the study was conducted inaccordance with the Declaration of Helsinki and the InternationalConference on Harmonization Guidelines for Good Clinical Practice. Allthe patients provided written informed consent before study entry. Theprincipal investigator (D.L.) and study sponsor (L.A.D.) wereresponsible for oversight of the study. Merck donated the study drug,reviewed the final drafts of the protocol and of this manuscript. Theclinical study was primarily funded through philanthropic support.

Study Design

This phase 2 trial was conducted using a Green-Dahlberg two-stage designand consisted of the three parallel cohorts described above. The studyagent, pembrolizumab (Merck), was administered at 10 mg/kg intravenouslyevery 14 days. Pembrolizumab is a humanized monoclonal anti-PD-1antibody of the IgG4/kappa isotype that blocks the interaction betweenPD-1 and its ligands, PD-L1 and PD-L2.

Safety assessments were performed before each treatment. Assessments oftotal tumor burden via measurements of serum biomarkers were performedat the start of each cycle. Radiologic assessments were made at 12 weeksand every 8 weeks thereafter. Further details concerning the clinicalprotocol are provided in the Example 3.

Analysis of Mismatch Repair Status

Tumors with genetic defects in MMR pathways are known to harborthousands of somatic mutations, especially in regions of repetitive DNAknown as microsatellites. The accumulation of mutations in these regionsof the genome is termed microsatellite instability (MSI)^(26-28.)MMR-status was assessed using the MSI Analysis System from Promega intumors, through the evaluation of selected microsatellite sequencesparticularly prone to copying errors when MMR is compromised²⁶⁻²⁸. SeeSupplementary Appendix for additional details.

Genomic & Bioinformatic Analyses

Primary tumor samples and matched normal peripheral-blood specimens wereobtained from a subset of subjects with MMR-deficient and others withMMR-proficient carcinomas where sufficient tumor tissue was availablefor exome sequencing³⁰ and HLA haplotyping. To assess the potential formutant peptide binding, somatic exome data combined with the individualpatient's MEW class I HLA haplotype was applied to the an epitopeprediction algorithm^(31,32). This algorithm provided an estimate of thetotal number of mutation-associated neoantigens in each tumor.Additional details are provided in the Supplementary Appendix (availableon line at New England Journal of Medicine; incorporated by referenceherein).

Statistical Analysis

The primary endpoints for Cohorts A and B were immune-related objectiveresponse rate (irORR) and immune-related progression-free survival(irPFS) rate at 20 weeks assessed using immune-related response criteria(irRC)³³. The primary endpoint for Cohort C was irPFS rate at 20 weeks.Immune-related criteria (i.e, criteria used to evaluate immune-basedtherapies) are based on radiographic responses, and unlike RECISTcriteria, capture extent of disease after disease progression; thesecriteria are defined and compared to RECIST v1.1 in FIG. 10 (Table 51).Response rate and PFS rate at 20 weeks were evaluated and reported inthis study using RECIST v1.1 and irRC (FIG. 10 (Table 51)). PFS andoverall survival was summarized by Kaplan-Meier method. Details of thehypothesis, the decision rules to reject the null hypotheses andearly-stopping rules for efficacy and futility, and statistical methodsare provided in the Supplementary Appendix.

Example 3

Supplementary Methods

Patients

To be eligible for participation in this study, patients had to be atleast 18 years of age, have histologically confirmed evidence ofpreviously-treated, progressive carcinoma. All patients underwent MMRstatus testing prior to enrollment. All patients had at least onemeasurable lesion as defined by the Response Evaluation Criteria inSolid Tumors (RECIST), version 1.1, an Eastern Cooperative OncologyGroup (ECOG) performance-status score of 0 or 1, and adequatehematologic, hepatic, and renal function. Eligible patients with CRCmust have received at least 2 prior cancer therapies and patients withother cancer types must have received at least 1 prior cancer therapy.Patients with untreated brain metastases, history of HIV, hepatitis B,hepatitis C, clinically significant ascites/effusions, or autoimmunedisease were excluded.

Study Oversight

Initial drafts of the manuscript were prepared by a subset of theauthors and all authors contributed to the final manuscript. All theauthors made the decision to submit the manuscript for publication. Theprincipal investigator and study sponsor vouch for the accuracy andcompleteness of the data reported as well as adherence to the protocol.

HLA Typing

HLA-A, HLA-B and HLA-C Sequence Based Typing can be divided into threedistinct steps, as described below. A generic, A*02 specific, B generic,B group specific, C generic and C*07 specific PCR and sequencing mixeswere made in the JHU core facility. Celera's AlleleSEQR HLA-B SequenceBased Typing kit was used for B generic SBT. The HLA-A typing scheme iscomposed of two PCR reactions, A generic and A*02 specific. A genericamplicon encompasses partial exon 1-partial exon 5. A*02 ampliconencompasses partial intron 1-partial exon 5. HLA-B typing scheme iscomposed of two PCR reactions, B generic and B group specific. The Bgeneric PCR is a multiplexed reaction containing two PCR ampliconsencompassing exon 2-exon 3 and exon 4-exon 7. B group specific ampliconencompasses partial intron 1-partial exon 5. HLA-C typing scheme iscomposed of two PCR reactions, C generic and C*07 specific. C genericand C*07 specific amplicons encompasses exons 1-7.

The specificity of the HLA-A and B PCR employed AmpliTaq Gold DNApolymerase. The GeneAmp High Fidelity enzyme is used for the HLA-C andC*07 PCR mixes. This enzyme is a mix of two polymerases: AmpliTaq DNApolymerase (non-proofreading polymerase) and a proofreading polymerase.This enzyme mix is necessary to produce efficient and robustamplification of the larger full length HLA-C amplicon.

PCR product purification was performed using Exonuclease I and ShrimpAlkaline Phosphatase The A generic and B generic amplicons werebi-directionally sequenced for exons 2,3,4. The C generic amplicon wasbi-directionally sequenced for exons 2,3 and sequenced in a singledirection for exons 1,4,5,6,7. A*02 specific, B group specific and C*07specific amplicons were sequenced in a single direction for exons 2,3.All sequencing reactions were performed with Big Dye Terminator V1.1from Applied Biosystems and sequenced with an ABI Prism 3500XL GeneticAnalyzer. Conexio Genomic's “Assign SBT” allele assignment software wasused to process the data files.

Mismatch Repair Status Testing^(1,2)

Six slides of tumor and normal (uninvolved lymph node or margin ofresection) were cut (5 microns each), deparaffinized (xylene), and onestained with hematoxylin and eosin (H+E). A tumor area containing atleast 20% neoplastic cells, designated by a board-certified AnatomicPathologist was macrodissected using the Pinpoint DNA isolation system(Zymo Research, Irvine, Calif.), digested in proteinase K for 8 hoursand DNA was isolated using a QIAamp DNA Mini Kit (Qiagen, Valencia,Calif.). MSI was assessed using the MSI Analysis System (Promega,Madison, Wis.), composed of 5 pseudomonomorphic mononucleotide repeats(BAT-25, BAT-26, NR-21, NR-24 and MONO-27) to detect MSI and2-pentanucleotide repeat loci (PentaC and PentaD) to confirm identitybetween normal and tumor samples, per manufacturer's instructions.Following amplification of 50-100 ng DNA, the fluorescent PCR productswere sized on an Applied Biosystems 3130xl capillary electrophoresisinstrument (Invitrogen, Calsbad, Calif.). Pentanucleotide loci confirmedidentity in all cases. Controls included water as a negative control anda mixture of 80% germline DNA with 20% MSI cancer DNA as a positivecontrol. The size in bases was determined for each microsatellite locusand tumors were designated as MSI if two or more mononucleotide locivaried in length compared to the germline DNA.

Sequencing Analysis

Samples

Samples provided as FFPE blocks or frozen tissue underwent pathologicalreview to determine tumor cellularity. Tumors were macrodissected toremove contaminating normal tissue, resulting in samples containing >20%neoplastic cells. Matched normal samples were provided as blood, salivaor normal tissue obtained from surgery.

Sample Preparation and Next-Generation Sequencing³

Sample preparation, library construction, exome capture, next generationsequencing, and bioinformatics analyses of tumor and normal samples wereperformed at Personal Genome Diagnostics, Inc. (Baltimore, Md.). Inbrief, DNA was extracted from frozen or formalin-fixed paraffin embedded(FFPE) tissue, along with matched blood or saliva samples using theQiagen DNA FFPE tissue kit or Qiagen DNA blood mini kit (Qiagen, CA).Genomic DNA from tumor and normal samples were fragmented and used forIllumina TruSeq library construction (Illumina, San Diego, Calif.)according to the manufacturer's instructions or as previouslydescribed4. Briefly, 50 nanograms (ng)-3 micrograms (μg) of genomic DNAin 100 microliters (μl) of TE was fragmented in a Covaris sonicator(Covaris, Woburn, Mass.) to a size of 150-450 bp. To remove fragmentssmaller than 150 bp, DNA was purified using Agencourt AMPure XP beads(Beckman Coulter, IN) in a ratio of 1.0 to 0.9 of PCR product to beadstwice and washed using 70% ethanol per the manufacturer's instructions.Purified, fragmented DNA was mixed with 36 μl of H2O, 10 μl of EndRepair Reaction Buffer, 5 μl of End Repair Enzyme Mix (cat #E6050, NEB,Ipswich, Mass.). The 100 μl end-repair mixture was incubated at 20° C.for 30 min, and purified using Agencourt AMPure XP beads (BeckmanCoulter, IN) in a ratio of 1.0 to 1.25 of PCR product to beads andwashed using 70% ethanol per the manufacturer's instructions. To A-tail,42 μl of end-repaired DNA was mixed with 5 μl of 10×dA Tailing ReactionBuffer and 3 μl of Klenow (exo-)(cat #E6053, NEB, Ipswich, Mass.). The50 μl mixture was incubated at 37° C. for 30 min and purified usingAgencourt AMPure XP beads (Beckman Coulter, IN) in a ratio of 1.0 to 1.0of PCR product to beads and washed using 70% ethanol per themanufacturer's instructions. For adaptor ligation, 25 μl of A-tailed DNAwas mixed with 6.7 μl of H2O, 3.3 μl of PE-adaptor (Illumina), 10 μl of5× Ligation buffer and 5 μl of Quick T4 DNA ligase (cat #E6056, NEB,Ipswich, Mass.). The ligation mixture was incubated at 20° C. for 15 minand purified using Agencourt AMPure XP beads (Beckman Coulter, IN) in aratio of 1.0 to 0.95 and 1.0 of PCR product to beads twice and washedusing 70% ethanol per the manufacturer's instructions. To obtain anamplified library, twelve PCRs of 25 μl each were set up, each including15.5 μl of H2O, 5 μl of 5×Phusion HF buffer, 0.5 μl of a dNTP mixcontaining 10 mM of each dNTP, 1.25 μl of DMSO, 0.25 μl of Illumina PEprimer #1, 0.25 μl of Illumina PE primer #2, 0.25 μl of Hotstart Phusionpolymerase, and 2 μl of the DNA. The PCR program used was: 98° C. for 2minutes; 12 cycles of 98° C. for 15 seconds, 65° C. for 30 seconds, 72°C. for 30 seconds; and 72° C. for 5 min. DNA was purified usingAgencourt AMPure XP beads (Beckman Coulter, IN) in a ratio of 1.0 to 1.0of PCR product to beads and washed using 70% ethanol per themanufacturer's instructions. Exonic or targeted regions were captured insolution using the Agilent SureSelect v.4 kit according to themanufacturer's instructions (Agilent, Santa Clara, Calif.). The capturedlibrary was then purified with a Qiagen MinElute column purification kitand eluted in 17 μl of 70° C. EB to obtain 15 μl of captured DNAlibrary. (5) The captured DNA library was amplified in the followingway: Eight 30 uL PCR reactions each containing 19 μl of H2O, 6 μl of 5×Phusion HF buffer, 0.6 μl of 10 mM dNTP, 1.5 μl of DMSO, 0.30 μl ofIllumina PE primer #1, 0.30 μl of Illumina PE primer #2, 0.30 μl ofHotstart Phusion polymerase, and 2 μl of captured exome library were setup. The PCR program used was: 98° C. for 30 seconds; 14 cycles (exome)or 16 cycles (targeted) of 98° C. for 10 seconds, 65° C. for 30 seconds,72° C. for 30 seconds; and 72° C. for 5 min. To purify PCR products, aNucleoSpin Extract II purification kit (Macherey-Nagel, P A) was usedfollowing the manufacturer's instructions. Paired-end sequencing,resulting in 100 bases from each end of the fragments for exomelibraries and 150 bases from each end of the fragment for targetedlibraries, was performed using Illumina HiSeq 2000/2500 and IlluminaMiSeq instrumentation (Illumina, San Diego, Calif.).

Primary Processing of Next-Generation Sequencing Data and Identificationof Putative Somatic Mutations3

Somatic mutations were identified using VariantDx custom software(Personal Genome Diagnostics, Baltimore, Md.) for identifying mutationsin matched tumor and normal samples. Prior to mutation calling, primaryprocessing of sequence data for both tumor and normal samples wereperformed using Illumina CASAVA software (v1.8), including masking ofadapter sequences. Sequence reads were aligned against the humanreference genome (version hg18) using ELAND with additional realignmentof select regions using the Needleman-Wunsch method 5. Candidate somaticmutations, consisting of point mutations, insertions, and deletions werethen identified using VariantDx across the either the whole exome orregions of interest. VariantDx examines sequence alignments of tumorsamples against a matched normal while applying filters to excludealignment and sequencing artifacts. In brief, an alignment filter wasapplied to exclude quality failed reads, unpaired reads, and poorlymapped reads in the tumor. A base quality filter was applied to limitinclusion of bases with reported phred quality score >30 for the tumorand >20 for the normal. A mutation in the tumor was identified as acandidate somatic mutation only when (i) distinct paired reads containedthe mutation in the tumor; (ii) the number of distinct paired readscontaining a particular mutation in the tumor was at least 10% of readpairs; (iii) the mismatched base was not present in >1% of the reads inthe matched normal sample as well as not present in a custom database ofcommon germline variants derived from dbSNP; and (iv) the position wascovered in both the tumor and normal at >150×. Mutations arising frommisplaced genome alignments, including paralogous sequences, wereidentified and excluded by searching the reference genome.

Candidate somatic mutations were further filtered based on geneannotation to identify those occurring in protein-coding regions.Functional consequences were predicted using snpEff and a customdatabase of CCDS, RefSeq and Ensembl annotations using the latesttranscript versions available on hg18 from UCSC (available atgenome.usc.edu). Predictions were ordered to prefer transcripts withcanonical start and stop codons and CCDS or Refseq transcripts overEnsembl when available. Finally mutations were filtered to excludeintronic and silent changes, while retaining mutations resulting inmissense mutations, nonsense mutations, frameshifts, or splice sitealterations. A manual visual inspection step was used to further removeartifactual changes.

Mutant Peptide Mhc Binding Prediction

Somatic frameshift, insertions, deletions, and missense mutationspredicted to result in an amino acid change were analyzed for potentialMHC class I binding based on the individual patient's HLA haplotype. Ourinitial analysis focused on HLA-A and HLA-B. Amino acid mutations werelinked to their corresponding CCDS accession number and in instanceswhere this was unavailable, either a Refseq or ensemble transcript wasused to extract the protein sequence. To identify 8 mer, 9 mer, and 10mer epitopes, amino acid fragments surrounding each mutation wereidentified. These 15, 17, and 19 mutant amino acid fragments wereanalyzed by the epitope prediction program NetMHC 3.4.6 Epitopes with apredicted affinity of <50 nm were considered to be strong potentialbinders and epitopes with a predicted affinity of <500 nm wereconsidered to be weak potential binders as suggested by the NetMHCgroup6.

To further refine the total neoantigen burden, we repeated that sameprocess for the complementary wild-type peptide for each mutant peptide.We then filtered for mutant peptides that were strong potential binderswhen the complementary wild-type peptide was predicted a weak potentialbinder. These mutant peptides are referred to as mutation-associatedneoantigens (MANA). In the event that a patient had a (e.g., cases 1, 17and 21) single MHC haplotype not supported by NetMHC 3.4, the individualhaplotype was not included in our analysis.

Statistical Methods

Design of the Trial⁷

This trial was conducted using a parallel two-stage design tosimultaneously evaluate the efficacy of MK-3475 and MSI as a treatmentselection marker for anti-PD-1 therapy. It consisted of two-stage phase2 studies in parallel in the three cohorts of patients described in thetext. The study agent, MK-3475, was administered at 10 mg/kgintravenously every 14 days.

For each of Cohort A and B, the co-primary endpoints wereprogression-free-survival (irPFS) at 20 weeks and objective response(irOR) assessed using immune related criteria. A step-down gatekeepingprocedure was used to preserve the overall type I error. A two-stageGreen-Dahlberg design was used to evaluate irPFS, with interim and finalanalysis after 15 and 25 patients, respectively. At stage 1, ≥1 of 15free-of-progression at 20 weeks were required to proceed to the secondstage, and ≥4 of 25 free-of-progression at 20 weeks were then requiredto proceed to test for irOR, with ≥4 of 25 responders (irCR or irPR)indicating promising efficacy in that cohort. Each cohort could beterminated for efficacy as soon as ≥4 free-of-progression at 20 weeksand ≥4 responses were confirmed, or be terminated for futility as soonas 0 of 15 in stage 1 were free-of-progression at 20 weeks or ≥22subjects had disease progression by 20 weeks. This design achieves 90%power to detect a 20-week irPFS rate of 25% and 80% power to detect anirOR rate (irORR) of 21%, with an overall type I error of 0.05 at thenull hypothesis of 20-week irPFS rate of 5% and irORR of 5%.

For Cohort C, the primary endpoint was irPFS at 20 weeks. A two-stageGreen-Dahlberg two-stage design was used, with an interim and finalanalysis after 14 and 21 patients; at stage 1, ≥1 of 14free-of-progression at 20 weeks were required to proceed to the secondstage, with ≥4 of 21 free-of-progression at 20 weeks at the endindicating adequate efficacy in Cohort C. The cohort could be terminatedas soon as ≥4 free-of-progression at 20 weeks were confirmed. The designhas 81% power to detect a 20-week irPFS rate of 25% with a 5% type Ierror at the null hypothesis of 20-week irPFS rate of 5%.

Statistical Analysis

Response and progression were evaluated using RECIST v1.1 and theimmune-related response criteria (irRC) adopted from Wolchok et al. 8,which uses the sum of the products of bidimensional tumor measurementsand incorporates new lesions into the sum. Progression-free survival(PFS) rates and irPFS rate at 20-weeks was estimated as the proportionof patients who were free-of-disease progression and alive at 20 weeksafter the initiation of pembrolizumab. Patients who had diseaseprogression prior to 20 weeks or were enrolled for >20 weeks at the timethe study data were collated were included in the analysis forestimating 20-week PFS (irPFS) rate. Patients who dropped out early dueto toxicities or worsening disease and therefore did not have 20-weektumor assessment were considered as having progressive disease. ORR(irORR) was the proportion of patients who achieved best overallresponse of CR or PR (irCR or irPR). Patients who were in the study longenough to have tumor response evaluations were included in the analysisfor estimating response rates. Among those who responded (CR or PR),duration of response was the time of first RECIST response to the timeof disease progression, and was censored at the last evaluable tumorassessment for responders who had not progressed.

PFS and irPFS were defined as the time from the date of initial dose tothe date of disease progression or the date of death due to any cause,whichever occurred first. PFS and irPFS were censored on the date of thelast evaluable tumor assessment documenting absence of progressivedisease for patients who were alive and progression-free. Overallsurvival (OS) was defined as the time from the date of initial dose todeath due to any cause. For patients who were still alive at the time ofanalysis, the OS time was censored on the last date the patients wereknown to be alive. Survival times were summarized by the Kaplan-Meiermethod. As a post hoc analysis, log-rank tests were used to compareCohort A and B and hazard ratios were estimated based on Cox models.

The association of percent CEA decline after 1 cycle with PFS or OS wasassessed using landmark analysis based on Cox regression models. Forcorrelative studies, non-parametric Wilcoxon test was used to comparemutational load between MMR-deficient and MMR-proficient patients. Theeffects of baseline mutational burden and immune markers on response andsurvival times were examined using logistic regression and Coxregression, respectively.

Immunohistochemistry & Image Analysis

The fraction of malignant cells exhibiting a membranous pattern of B7-H1expression and the percentage at the invasive front were quantified bythree pathologists (R.A.A., F.B., and J.M.T.) as previouslyreported9,10. Image analysis was used to determine the number of CD8diaminobenzidine (DAB)-stained cells. Using the H&E-stained slide foreach case, we identified the following regions: i) tumor, ii) invasivefront (the boundary between malignant and non-malignant tissue), andiii) normal tissue. The CD8-stained slides were scanned at 20×equivalent magnification (0.49 micrometers per pixel) on an AperioScanScope AT. Regions corresponding to tumor, invasive front and normaltissue (above, from the H&E) were annotated on separate layers usingAperio ImageScope v12.1.0.5029.

CD8-positive lymphocyte density was calculated in each of the aboveregions using a custom algorithm implemented in PIP11. Results wereconverted to Deepzoom images using the VIPS library12 and visualizedusing the OpenSeadragon viewer (available at openseadragon.github.io).

REFERENCES FOR EXAMPLE 3 ONLY

-   1. Bacher J W, Flanagan L A, Smalley R L, et al. Development of a    fluorescent multiplex assay for detection of MSI-High tumors.    Disease markers 2004; 20:237-50.-   2. Murphy K M, Zhang S, Geiger T, et al. Comparison of the    microsatellite instability analysis system and the Bethesda panel    for the determination of microsatellite instability in colorectal    cancers. The Journal of molecular diagnostics: JMD 2006; 8:305-11.-   3. Jones S, Anagnostou V, Lytle K, et al. Personalized genomic    analyses for cancer mutation discovery and interpretation. Science    translational medicine 2015; 7:283ra53.-   4. Sausen M, Leary R J, Jones S, et al. Integrated genomic analyses    identify ARID1A and ARID1B alterations in the childhood cancer    neuroblastoma. Nature genetics 2013; 45:12-7.-   5. Needleman S B, Wunsch C D. A general method applicable to the    search for similarities in the amino acid sequence of two proteins.    Journal of molecular biology 1970; 48:443-53.-   6. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M.    NetMHC-3.0: accurate web accessible predictions of human, mouse and    monkey MHC class I affinities for peptides of length 8-11. Nucleic    acids research 2008; 36:W509-12.-   7. Buyse M, Michiels S, Sargent D J, Grothey A, Matheson A, de    Gramont A. Integrating biomarkers in clinical trials. Expert review    of molecular diagnostics 2011; 11:171-82.-   8. Wolchok J D, Hoos A, O'Day S, et al. Guidelines for the    evaluation of immune therapy activity in solid tumors:    immune-related response criteria. Clinical cancer research: an    official journal of the American Association for Cancer Research    2009; 15:7412-20.-   9. Llosa N J, Cruise M, Tam A, et al. The vigorous immune    microenvironment of microsatellite instable colon cancer is balanced    by multiple counter-inhibitory checkpoints. Cancer Discov    2015:43-51.-   10. Taube J M, Anders R A, Young G D, et al. Colocalization of    Inflammatory Response with B7-H1 Expression in Human Melanocytic    Lesions Supports an Adaptive Resistance Mechanism of Immune Escape.    Science Translational Medicine 2012; 4:127ra37.-   11. Cuka N, Hempel H, Sfanos K, De Marzo A, Cornish T. PIP: An Open    Source Framework for Multithreaded Image Analysis of Whole Slide    Images. LABORATORY INVESTIGATION 2014; 94:398A-A.-   12. Cupitt J, Martinez K. VIPS: an image processing system for large    images. Electronic Imaging: Science & Technology; 1996:    International Society for Optics and Photonics. p. 19-28.

Example 4

Patients

41 consecutive patients were enrolled and treated between September 2013and January 2015. (Table 1). Recruitment included patients in pursuit ofa clinical trial option who were known to have tumors with mismatchrepair, or who had tumors of unknown status who were then tested. Onepatient in the MMR-deficient CRC cohort was enrolled under an IRBeligibility waiver allowing a grade 3 bilirubin level. A total of 32 CRCpatients were enrolled into Cohorts A and B. All CRC patients received≥2 prior chemotherapy regimens (median=4) except for one MMR-proficientpatient who had received one chemotherapeutic and one (non-PD1-based)immunotherapeutic regimen.

Nine subjects diagnosed with MMR-deficient solid tumors other than CRCwere enrolled onto Cohort C. All Cohort C patients received ≥1 priorcancer treatments (median=2).

Example 5

Primary Endpoint Evaluation

The irORR and irPFS at 20 weeks (FIG. 11 (Table S2)) for Cohort A were40% (4 of 10 patients; 95% CI, 12 to 74%) and 78% (7 of 9 patients; 95%CI, 40 to 97%) and for Cohort C were 71% (5 of 7 patients; 95% CI, 29 to96%) and 67% (4 of 6 patients; 95% CI, 22 to 96%). In Cohort B,comprised of patients with MMR-proficient CRCs, irORR and 20-week irPFSwere 0% (95% CI, 0 to 20%) and 11% (2 of 18 patients; 95% CI, 1 to 35%).Both the MMR-deficient cohorts A and C reached their predefined earlystopping rule for efficacy when four subjects were free-of-diseaseprogression at 20 weeks and four objective responses were observed basedon immune-related response criteria (FIG. 11 (Table S2); available online at New England Journal of Medicine; incorporated by referenceherein; and supplementary methods, above).

The median time of follow-up for patients was 32 weeks (range, 5-51weeks) for patients with MMR-deficient CRC (Cohort A), 12 weeks (range,2-56 weeks) for patients with MMR-proficient CRC (Cohort B) and 12 weeks(range, 4-42 weeks) for patients with MMR-deficient non-CRC tumors(Cohort C). All patients evaluable for 20-week irPFS were followed forat least 20 weeks.

Example 6

Radiographic Evaluation

Of the ten evaluable MMR-deficient CRC patients in Cohort A, four (40%;95% CI, 12-74%) achieved objective responses by RECIST criteria (Table2, FIG. 1 and FIG. 3 (S2)). Patients were considered not evaluableunless they underwent a 12-week scan. The disease control rate wasdefined as the fraction of patients who achieved an objective responseor whose disease was stable, and was 90% in Cohort A (9 of 10 patients;95% CI, 55-100%).

Of the seven evaluable patients with MMR-deficient cancer types otherthan CRC enrolled in Cohort C, five (71%; 95% CI, 29-96%) achievedobjective responses (Table 2, FIG. 3 (S2) and FIG. 1 ) using RECISTcriteria and the disease control rate was 71% (5 of 7 patients; 95% CI,29-96%).

Patients in Cohort C responded faster than patients in Cohort A (mediantime to response by RECIST of 12 vs. 28 weeks, p=0.03). Furthermore, allsix MMR-deficient tumors that were not associated with Lynch syndrome(100%) achieved an objective response, whereas only three of eleventumors (27%) associated with Lynch Syndrome responded (Table S3;p=0.009; available on-line at New England Journal of Medicine; andincorporated by reference herein). No other baseline characteristicsshowed statistically significant association with objective responses.

Of the 18 patients with MMR-proficient CRCs in Cohort B, no objectiveresponses were observed (Table 2, FIG. 3 (S2) and FIG. 1 ) using RECISTcriteria and the disease control rate was 11% (2 of 18 patients; 95% CI,1 to 35%).

All patients who achieved a response by RECIST criteria (FIG. 11 (Table2)) also achieved a response by immune-related response criteria (FIG.11 (Table S2)).

Example 7

Survival

In Cohort A, the patients with MMR-deficient CRC, medianprogression-free survival (PFS) and median overall survival (OS) werenot reached (FIG. 2 ). In contrast, the patients with MMR-proficientcancers in Cohort B achieved a PFS of only 2.2 months (95% CI, 1.4-2.8)and a median OS of 5.0 months (95% CI, 3.0 to not estimable). In CohortC (MMR-deficient non-CRC), the median PFS was 5.4 months (95% CI, 3 tonot estimable) and the median OS was not reached.

A post hoc (FIG. 2 ) comparison of the MMR-deficient and proficient CRCcohorts showed hazard ratios (HR) for disease progression (HR=0.10; 95%CI, 0.03-0.37; p<0.001) and overall survival (HR=0.22; 95% CI,0.05-1.00; p=0.05), favoring patients with MMR-deficient CRC.

To evaluate whether the difference in survival might be due toprognostic differences, we measured the duration of time patients hadbeen diagnosed with metastatic disease and the clinical performance ofpatients on their previous regimen prior to enrollment. We found thatthere was no significant difference between MMR-deficient vs.MMR-proficient CRC patients with respect to their duration of metastaticdisease (p=0.77; Log-rank test) or median PFS (p=0.60, Log-rank test) ontheir prior regimens (FIG. 4 (S3)). We also performed an additionalmultivariate analysis of PFS and OS to examine the difference inoutcomes between MMR-deficient CRC and MMR-proficient tumors adjustingfor elapsed time since initial diagnosis. The magnitude of the hazardratios for PFS (HR 0.04, 95% CI 0.01-0.21, P<0.001) and OS (HR 0.18, 95%CI 0.03-1.01, P=0.05), representing the different effect ofpembrolizumab between MMR-deficient and MMR-proficient tumors, wasmaintained after adjusting for this potential difference.

Example 8

Safety Assessment

Adverse events occurring in >5% of patients are listed in Table 3.Select adverse events included rash/pruritus (24%),thyroiditis/hypothyroidism/hypophysitis (10%), and asymptomaticpancreatitis (15%). While the numbers were small, thyroid functionabnormalities were limited to the MMR-deficient cohorts (Table 3).

Example 9

Tumor Markers

In the two CRC cohorts, baseline CEA levels were evaluable and above theupper limit of normal (3 mg/dl), in 29 of 32 patients prior toenrollment. Major CEA declines occurred in seven of the ten patientswith MMR-deficient CRC and in none of the 19 patients withMMR-proficient CRCin which CEA was evaluable (FIG. 1 and FIG. 5 (S4)).In non-CRC MMR-deficient patients, tumor marker levels (CEA, CA19-9 orCA-125) were elevated above the upper limit of normal in four patients.CA19-9 or CA-125 declines of >70% occurred in three of these fourpatients. Tumor marker kinetics of all 3 cohorts are shown in FIG. 1 .The level of CEA decline after 1 dose (between days 14 and 28) ofpembrolizumab was predictive of both progression-free (p=0.01) andoverall survival outcomes (p=0.02). The CEA response occurred well inadvance of radiographic confirmation of disease control (range, 10 to 35weeks). In contrast, patients who progressed showed rapid biomarkerelevation within 30 days of initiating therapy. Thus, changes in CEAlevels significantly preceded and correlated with ultimate radiographicchanges.

Example 10

Genomic Analysis

Analysis of whole-exome sequences showed an average of 1,782 somaticmutations per tumor in MMR-deficient patients (n=9) compared with 73mutations per tumor in MMR-proficient patients (n=6) (non-parametricWilcoxon test, p=0.007) (FIGS. 6A-6B (S5); see also Table S3 which isavailable on-line at New England Journal of Medicine; incorporated byreference herein). Most (63%) of these mutations are predicted to alteramino acids.

These mutations were then assessed for their immunogenic potential inthe context of each patient's individual MHC haplotype. We therebyidentified an average of 578 and 21 potential mutation-associatedneoantigens from the tumors of MMR-deficient and MMR-proficientpatients, respectively (Table S3; which is available on-line at NewEngland Journal of Medicine; incorporated by reference herein). Thefraction of potential mutation-associated neoantigens among all somaticmutations was similar in both cohorts (averaging 32% and 29% inMMR-deficient and -proficient patients, respectively). High numbers ofsomatic mutations and potential mutation-associated neoantigens wereassociated with improved progression-free survival and with a trend infavor of objective response (FIG. 13 (S5) and FIG. 12 (Table S4); alsoavailable on line at New England Journal of Medicine; incorporated byreference herein).

Example 11

Immunohistochemistry

Expression of CD8 and PD-L1 were evaluated by immunohistochemistrywithin the tumor and at the invasive fronts of the tumor in the 30 casesin which tumor tissue was available (FIG. 7 (S6); also available on lineat New England Journal of Medicine; incorporated by reference herein).Tumors from patients in Cohorts A and C contained a greater density ofCD8-positive lymphoid cells than did tumors from Cohort B patients (FIG.8 (S7); p=0.10) and CD8-labeling was associated with a trend favoringobjective response and stable disease (FIG. 9 (S8) and FIG. 13 (TableS5); also available on line at New England Journal of Medicine;incorporated by reference herein). This CD8-positive lymphoid infiltratewas especially prominent at the invasive fronts of the tumors (FIG. 8(S7); p=0.04). Significant membranous PD-L1 expression only occurred inMMR-deficient patients and was prominent on tumor infiltratinglymphocytes (TILs) and tumor-associated macrophages located at thetumors' invasive fronts (FIG. 8 (S7); p=0.04). Expression of CD8 andPD-L1 were not statistically associated with PFS or OS (FIG. 13 (TableS5)).

TABLE 1 Demographic and Baseline Characteristics of Patients MMR- MRC-MMR- deficient proficient deficient CRC CRC P non-CRC Characteristic n =11 n = 21 values¹ n = 9 Age—years median 46 61 0.02 57 range (24-65)(32-79) (34-92) Sex—no. (%) Female 5(45)  8(38) 0.72 4(44) Male 6(55)13(62) 5(56) Race—no. (%) white 8(73) 17(81) 0.66 8(89) black 1(9)  3(14) 0(0)  other 2(18) 1(5) 1(11) ECOG Performance Status—no. (%)² 00(0)  6(29) 0.07 2(22) 1 11(100) 15(71) 7(78) Diagnosis—no. (%) Colon9(82) 18(86) >0.99 0(0)  Rectal 2(18)  3(14) 0(0) Ampullary/Cholangiocarcinoma 0(0)  N/A 4(44) Endometrial 0(0)  N/A 2(22)Small bowel 0(0)  N/A 2(22) Gastric 0(0)  N/A 1(11) Histology—no. (%)Well/moderately differentiated 7(64) 18(86) 0.20 4(44) Poorlydifferentiated 4(36)  3(14) 3(33) Other 0(0)  0(0) 2(22) Stage IV—no.(%) (11)100  21(100) >0.99  9(100) Liver metastases—no. (%) 6(55)11(52) >0.99 6(67) Time since first diagnosis—months median 31 58 0.0723 range  6-95  27-192  2-105 Prior systemic therapies—no. (%) 0 0(0) 0(0) 0.89 1(11) 2 3(27)  4(19) 5(56) 3 3(27)  5(24) 1(11) >4 5(45)12(57) 2(22) Detected germline mutation or known Lynch—no. (%) Yes 9(82)0(0) <0.001 4(44) No 2(18)  21(100) 4(44) Unknown 0(0)  0(0) 1(11) BRAFwild type—no. (%) Yes 8(73) 11(52) 0.64 4(44) No 0(0)  1(5) 0(0) Unknown 3(27)  9(43) 5(56) KRAS wild type—no. (%) Yes 6(55) 13(62) 0.724(44) No 5(45)  8(38) 1(11) Unknown 0(0)  0(0) 4(44) MMR, mismatchrepair; CRC, colorectal cancer ¹MMR-deficient CRC versus MMR-proficientCRC ²ECOG, Eastern Cooperative Oncology Group

TABLE 2 Objective RECIST responses MMR-deficient MRC-proficientMMR-deficient CRC CRC non-CRC Type of Response—no. (%) n = 10 n = 18 n =7 Complete Response 0(0)  0(0)   1(14)¹ Partial Response 4(40) 0(0)  4(57)² Stable Disease (Week 12) 5(50)  2(11) 0(0) Progressive Disease1(10) 11(61)  2(29) Not Evaluable³ 0(0)   5(28) 0(0) Objective ResponseRate (%) 40 0 71 95% CI 12-74 0-19 29-96 Disease Control Rate (%)⁴ 90 1171 95% CI  55-100 1-35 29-96 Duration of Response—median weeks Notreached N/A⁵ Not reached Time to Response, median weeks (range) 28(13-35) N/A⁵ 11 (10-13) ¹Originally PR at 12 weeks that was converted toCR at 20 weeks ²One PR at 12 weeks ³Patients were considered notevaluable if they did not undergo a 12 week scan due to clinicalprogression. ⁴The rate of disease control was defined as the percentageof patients who had a complete response, partial response or stabledisease for 12 weeks or more. ⁵No responses recorded for MMR-proficientCRC patients

TABLE 3 Drug-Related Adverse Events All Grades Grade 3 or 4 Event—no(%)¹ N = 41 N = 41 Any 40(98)  17(41) Blood and Lymphatic Anemia 8(20) 7(17) Lymphopenia 8(20)  8(20) Cardiac Sinus tachycardia 4(10) 0Dermatologic Dry skin 5(12) 0 Rash/pruritis 10(24)  0 EndocrineDisorders Thyroiditis/Hypothyroidism/Hypophysitis 4(10) 0Gastrointestinal Abdominal Pain 10(24)  0 Anorexia 4(10) 0 Constipation8(20) 0 Diarrhea 10(24)  2(5) Dry mouth 5(12) 0 Nausea 5(12) 0 BowelObstruction 3(7)  3(7) Hepatobiliary ALT, elevated 3(7)  2(5)Pancreatitis² 6(15) 0 Metabolism and Nutrition Hypoalbuminemia 4(10) 4(10) Hyponatremia 3(7)  3(7) Musculoskeletal Arthralgia 7(17) 0Myalgia 6(15) 0 Nervous System Dizziness 4(10) 0 Headache 7(17) 0Psychiatric Insomnia 3(7)  0 Respiratory³ Allergic Rhinitis 12(29)  0Cough 4(10) 0 Dyspnea 6(15) 0 Upper Respiratory Infection 3(7)  0 OtherCold intolerance 6(15) 0 Edema 4(10) 0 Fatigue 13(32)  0 Fever 5(12) 0Pain 14(34)  0 ¹Adverse Events occurring in greater than 5% of patients²All cases of pancreatitis were asymptomatic ³One incidence ofpneumonitis (2%)

REFERENCES

The disclosure of each reference cited is expressly incorporated herein.

-   1. Nishimura H, Okazaki T, Tanaka Y, et al. Autoimmune Dilated    Cardiomyopathy in PD-1 Receptor-Deficient Mice. Science 2001;    291:319-22.-   2. Chen L. Co-inhibitory molecules of the B7-CD28 family in the    control of T-cell immunity. Nat Rev Immunol 2004; 4:336-47.-   3. Nishimura H, Nose M, Hiai H, Minato N, Honjo T. Development of    Lupus-like Autoimmune Diseases by Disruption of the PD-1 Gene    Encoding an ITIM Motif-Carrying Immunoreceptor. Immunity 1999;    11:141-51.-   4. Ansell S M, Lesokhin A M, Borrello I, et al. PD-1 Blockade with    Nivolumab in Relapsed or Refractory Hodgkin's Lymphoma. The New    England journal of medicine 2015; 372:311-9.-   5. Hamid O, Robert C, Daud A, et al. Safety and tumor responses with    lambrolizumab (anti-PD-1) in melanoma. The New England journal of    medicine 2013; 369:134-44.-   6. Herbst R S, Soria J C, Kowanetz M, et al. Predictive correlates    of response to the anti-PD-L1 antibody MPDL3280A in cancer patients.    Nature 2014; 515:563-7.-   7. Powles T, Eder J P, Fine G D, et al. MPDL3280A (anti-PD-L1)    treatment leads to clinical activity in metastatic bladder cancer.    Nature 2014; 515:558-62.-   8. Topalian S L, Sznol M, McDermott D F, et al. Survival, durable    tumor remission, and long-term safety in patients with advanced    melanoma receiving nivolumab. Journal of clinical oncology: official    journal of the American Society of Clinical Oncology 2014;    32:1020-30.-   9. Brahmer J R, Tykodi S S, Chow L Q, et al. Safety and activity of    anti-PD-L1 antibody in patients with advanced cancer. The New    England journal of medicine 2012; 366:2455-65.-   10. Topalian S L, Hodi F S, Brahmer J R, et al. Safety, activity,    and immune correlates of anti-PD-1 antibody in cancer. The New    England journal of medicine 2012; 366:2443-54.-   11. Taube J M, Klein A, Brahmer J R, et al. Association of PD-1,    PD-1 ligands, and other features of the tumor immune    microenvironment with response to anti-PD-1 therapy. Clinical cancer    research: an official journal of the American Association for Cancer    Research 2014; 20:5064-74.-   12. Brahmer J R, Drake C G, Wollner I, et al. Phase I study of    single-agent anti-programmed death-1 (MDX-1106) in refractory solid    tumors: safety, clinical activity, pharmacodynamics, and immunologic    correlates. Journal of clinical oncology: official journal of the    American Society of Clinical Oncology 2010; 28:3167-75.-   13. Koopman M, Kortman G A M, Mekenkamp L, et al. Deficient mismatch    repair system in patients with sporadic advanced colorectal cancer.    Br J Cancer 0000; 100:266-73.-   14. Goldstein J, Tran B, Ensor J, et al. Multicenter retrospective    analysis of metastatic colorectal cancer (CRC) with high-level    microsatellite instability (MSI-H). Annals of oncology: official    journal of the European Society for Medical Oncology/ESMO 2014;    25:1032-8.-   15. Segal N H, Parsons D W, Peggs K S, et al. Epitope landscape in    breast and colorectal cancer. Cancer research 2008; 68:889-92.-   16. Timmermann B, Kerick M, Roehr C, et al. Somatic mutation    profiles of MSI and MSS colorectal cancer identified by whole exome    next generation sequencing and bioinformatics analysis. PloS one    2010; 5:e15661.-   17. Eshleman J R, Lang E Z, Bowerfind G K, et al. Increased mutation    rate at the hprt locus accompanies microsatellite instability in    colon cancer. Oncogene 1995; 10:33-7.-   18. Comprehensive molecular characterization of human colon and    rectal cancer. Nature 2012; 487:330-7.-   19. Dolcetti R, Viel A, Doglioni C, et al. High prevalence of    activated intraepithelial cytotoxic T lymphocytes and increased    neoplastic cell apoptosis in colorectal carcinomas with    microsatellite instability. The American journal of pathology 1999;    154:1805-13.-   20. Alexander J, Watanabe T, Wu T T, Rashid A, Li S, Hamilton S R.

Histopathological identification of colon cancer with microsatelliteinstability. The American journal of pathology 2001; 158:527-35.

-   21. Smyrk T C, Watson P, Kaul K, Lynch H T. Tumor-infiltrating    lymphocytes are a marker for microsatellite instability in    colorectal carcinoma. Cancer 2001; 91:2417-22.-   22. Young J, Simms L A, Biden K G, et al. Features of colorectal    cancers with high-level microsatellite instability occurring in    familial and sporadic settings: parallel pathways of tumorigenesis.    The American journal of pathology 2001; 159:2107-16.-   23. Berger M F, Hodis E, Heffernan T P, et al. Melanoma genome    sequencing reveals frequent PREX2 mutations. Nature 2012; 485:502-6.-   24. Lee W, Jiang Z, Liu J, et al. The mutation spectrum revealed by    paired genome sequences from a lung cancer patient. Nature 2010;    465:473-7.-   25. Lipson E J, Sharfman W H, Drake C G, et al. Durable cancer    regression off-treatment and effective reinduction therapy with an    anti-PD-1 antibody. Clinical cancer research: an official journal of    the American Association for Cancer Research 2013; 19:462-8.-   26. Boland C R, Goel A. Microsatellite instability in colorectal    cancer. Gastroenterology 2010; 138:2073-87 e3.-   27. Lynch H T, de la Chapelle A. Hereditary colorectal cancer. The    New England journal of medicine 2003; 348:919-32.-   28. Yamamoto H, Imai K, Perucho M. Gastrointestinal cancer of the    microsatellite mutator phenotype pathway. Journal of    gastroenterology 2002; 37:153-63.-   29. Herman J G, Umar A, Polyak K, et al. Incidence and functional    consequences of hMLH1 promoter hypermethylation in colorectal    carcinoma. Proceedings of the National Academy of Sciences of the    United States of America 1998; 95:6870-5.-   30. Jones S, Anagnostou V, Lytle K, et al. Personalized genomic    analyses for cancer mutation discovery and interpretation. Science    translational medicine 2015; 7:283ra53.-   31. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M.    NetMHC-3.0: accurate web accessible predictions of human, mouse and    monkey MEW class I affinities for peptides of length 8-11. Nucleic    acids research 2008; 36:W509-12.-   32. Lundegaard C, Lund O, Nielsen M. Accurate approximation method    for prediction of class I MEW affinities for peptides of length 8,    10 and 11 using prediction tools trained on 9 mers. Bioinformatics    2008; 24:1397-8.-   33. Wolchok J D, Hoos A, O'Day S, et al. Guidelines for the    evaluation of immune therapy activity in solid tumors:    immune-related response criteria. Clinical cancer research: an    official journal of the American Association for Cancer Research    2009; 15:7412-20.-   34. Maple J T, Smyrk T C, Boardman L A, Johnson R A, Thibodeau S N,    Chari S T. Defective DNA mismatch repair in long-term (> or =3    years) survivors with pancreatic cancer. Pancreatology 2005;    5:220-7; discussion 7-8.-   35. Meltzer S J, Yin J, Manin B, et al. Microsatellite instability    occurs frequently and in both diploid and aneuploid cell populations    of Barrett's-associated esophageal adenocarcinomas. Cancer research    1994; 54:3379-82.-   36. Nakata B, Wang Y Q, Yashiro M, et al. Prognostic value of    microsatellite instability in resectable pancreatic cancer. Clinical    cancer research: an official journal of the American Association for    Cancer Research 2002; 8:2536-40.-   37. Comprehensive molecular characterization of gastric    adenocarcinoma. Nature 2014; 513:202-9.-   38. Agaram N P, Shia J, Tang L H, Klimstra D S. DNA mismatch repair    deficiency in ampullary carcinoma: a morphologic and    immunohistochemical study of 54 cases. American journal of clinical    pathology 2010; 133:772-80.-   39. Kandoth C, Schultz N, Cherniack A D, et al. Integrated genomic    characterization of endometrial carcinoma. Nature 2013; 497:67-73.-   40. Garg K, Leitao MINI, Jr., Kauff N D, et al. Selection of    endometrial carcinomas for DNA mismatch repair protein    immunohistochemistry using patient age and tumor morphology enhances    detection of mismatch repair abnormalities. The American journal of    surgical pathology 2009; 33:925-33.-   41. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for    clinical response to CTLA-4 blockade in melanoma. The New England    journal of medicine 2014; 371:2189-99.-   42. Williams A S, Huang W Y. The analysis of microsatellite    instability in extracolonic gastrointestinal malignancy. Pathology    2013; 45:540-52.-   43. Jones S, Emmerson P, Maynard J, et al. Biallelic germline    mutations in MYH predispose to multiple colorectal adenoma and    somatic G:C→T:A mutations. Human Molecular Genetics 2002; 11:2961-7.-   44. Palles C, Cazier J-B, Howarth K M, et al. Germline mutations    affecting the proofreading domains of POLE and POLD1 predispose to    colorectal adenomas and carcinomas. Nature genetics 2013; 45:136-44.-   45. Bodmer W, Bishop T, Karran P. Genetic steps in colorectal    cancer. Nature genetics 1994; 6:217-9.-   46. Kim H, Jen J, Vogelstein B, Hamilton S R. Clinical and    pathological characteristics of sporadic colorectal carcinomas with    DNA replication errors in microsatellite sequences. The American    journal of pathology 1994; 145:148-56.-   47. Llosa N J, Cruise M, Tam A, et al. The vigorous immune    microenvironment of microsatellite instable colon cancer is balanced    by multiple counter-inhibitory checkpoints. Cancer Discov    2015:43-51. [This disclosure was made by some of the joint    inventors.]-   48. Rizvi N A, Hellmann M D, Snyder A, et al. Mutational landscape    determines sensitivity to PD-1 blockade in non-small cell lung    cancer. Science 2015.-   49. Gubin M M, Zhang X, Schuster H, et al. Checkpoint blockade    cancer immunotherapy targets tumour-specific mutant antigens. Nature    2014; 515:577-81.-   50. Linnemann C, van Buuren M M, Bies L, et al. High-throughput    epitope discovery reveals frequent recognition of neo-antigens by    CD4+ T cells in human melanoma. Nature medicine 2015; 21:81-5.-   51. Lipson E J, Velculescu V E, Pritchard T S, et al. Circulating    tumor DNA analysis as a real-time method for monitoring tumor burden    in melanoma patients undergoing treatment with immune checkpoint    blockade. Journal for immunotherapy of cancer 2014; 2:42.-   52. Diaz L A, Jr., Bardelli A. Liquid biopsies: genotyping    circulating tumor DNA. Journal of clinical oncology: official    journal of the American Society of Clinical Oncology 2014;    32:579-86.-   53. Yadav M, Jhunjhunwala S, Phung Q T, et al. Predicting    immunogenic tumour mutations by combining mass spectrometry and    exome sequencing. Nature 2014; 515:572-6.

We claim:
 1. A method for treating a patient having a solid tumorselected from the group consisting of: endometrial cancer, small bowelcancer, gastric cancer, ampullary cancer, cholangiocarcinoma, pancreaticcancer, prostate cancer, breast cancer, esophageal cancer, liver cancer,ovarian cancer, uterine cancer, cervical cancer, bladder cancer,testicular cancer and oral cancer, the method comprising: in response todetermining that the solid tumor is microsatellite instability high orDNA mismatch repair deficient, treating a patient having a solid tumorselected from the group consisting of: endometrial cancer, small bowelcancer, gastric cancer, ampullary cancer, cholangiocarcinoma, pancreaticcancer, prostate cancer, breast cancer, esophageal cancer, liver cancer,ovarian cancer, uterine cancer, cervical cancer, bladder cancer,testicular cancer and oral cancer with a therapeutically effectiveamount of pembrolizumab based on a determination that the solid tumorhas progressed following at least one prior cancer treatment, andfurther based on previous testing of a biological sample obtained fromthe patient that the patient's solid tumor exhibits at least one markerfor high microsatellite instability or DNA mismatch repair deficiency.2. The method of claim 1, wherein the biological sample is tumor tissuefrom the patient.
 3. The method of claim 1, wherein the biologicalsample is a body fluid from the patient.
 4. The method of claim 1,wherein the solid tumor is microsatellite instability high.
 5. Themethod of claim 1, wherein the solid tumor is DNA mismatch repairdeficient.
 6. The method of claim 1, wherein the solid tumor ismetastatic.
 7. The method of claim 1, wherein the pembrolizumab isadministered to the patient intravenously.
 8. The method of claim 1,wherein the at least one marker comprises BAT-25, BAT-26, MONO-27, NR-21or NR-24.
 9. The method of claim 1, wherein the solid tumor isendometrial cancer, small bowel cancer, gastric cancer, ampullary canceror cholangiocarcinoma.
 10. The method of claim 1, wherein the solidtumor is pancreatic cancer, prostate cancer, breast cancer, esophagealcancer, liver cancer, ovarian cancer, uterine cancer, cervical cancer,bladder cancer, testicular cancer or oral cancer.
 11. A method forreducing the risk ofprogression of a solid tumor selected from the groupconsisting of: endometrial cancer, small bowel cancer, gastric cancer,ampullary cancer, cholangiocarcinoma, pancreatic cancer, prostatecancer, breast cancer, esophageal cancer, liver cancer, ovarian cancer,uterine cancer, cervical cancer, bladder cancer, testicular cancer andoral cancer that has progressed following at least one prior treatmentin a patient, the method comprising: in response to determining that thesolid tumor is microsatellite instability high or DNA mismatch repairdeficient, treating the patient with a therapeutically effective amountof pembrolizumab based on previous testing of a biological sampleobtained from the patient that the patient's solid tumor exhibits atleast one marker for high microsatellite instability or DNA mismatchrepair deficiency.
 12. The method of claim 11, wherein the biologicalsample was tumor tissue from the patient.
 13. The method of claim 11,wherein the biological sample was a body fluid from the patient.
 14. Themethod of claim 11, wherein the solid tumor is microsatelliteinstability high.
 15. The method of claim 11, wherein the solid tumor isDNA mismatch repair deficient.
 16. The method of claim 11, wherein thesolid tumor is metastatic.
 17. The method of claim 11, wherein thepembrolizumab is administered to the patient intravenously.
 18. Themethod of claim 11, wherein the previous testing comprised assessing oneor more of BAT-25, BAT-26, MONO-27, NR-21 and NR-24.
 19. The method ofclaim 11, wherein the solid tumor is endometrial cancer, small bowelcancer, gastric cancer, ampullary cancer or cholangiocarcinoma.
 20. Themethod of claim 11, wherein the solid tumor is pancreatic cancer,prostate cancer, breast cancer, esophageal cancer, liver cancer, ovariancancer, uterine cancer, cervical cancer, bladder cancer, testicularcancer or oral cancer.
 21. The method of claim 1, wherein the solidtumor is endometrial cancer.
 22. The method of claim 21, wherein theendometrial cancer is microsatellite instability high.
 23. The method ofclaim 21, wherein the endometrial cancer is DNA mismatch repairdeficient.
 24. The method of claim 21, wherein the solid tumor ismetastatic endometrial cancer.
 25. The method of claim 11, wherein thesolid tumor is endometrial cancer.
 26. The method of claim 25, whereinthe endometrial cancer is microsatellite instability high.
 27. Themethod of claim 25, wherein the endometrial cancer is DNA mismatchrepair deficient.
 28. The method of claim 25, wherein the solid tumor ismetastatic endometrial cancer.